A key goal of investors, traders, journalists, and others who are in some way connected with securities markets or other markets is to determine market performance overall, and how it effects themselves and others. This inquiry is complicated by the fact that, on a given day, the market as a whole may be up, a particular market sector (e.g., technology stocks) may be down, but a particular stock within that sector (e.g., Google) may be up. One conventional approach of objectively summarizing and benchmarking market performance with one or two indices (e.g., Dow Jones Industrial Average (DJIA)) obfuscates much of the detail needed by the market participants and observers. On the other extreme, another conventional presentation of market information is a list of stock prices such as what is found in a daily newspaper. The drawback, however, is the difficulty in collectively presenting a large amount of individual current statistics for items while summarizing the overall dynamic state of the information in a way that allows the user to interact with the data quickly at the individual, grouped and summary levels. Another approach employs a conventional heat map, which is a type of graphical representation of data where the individual values in a matrix are represented as colors. However, it is difficult to dynamically represent the multi-faceted relationships, sub-relationships, and pertinent data of individual items, related items and the information or market in aggregate using a conventional heat map.
A further drawback is each individual's information requirements and assessments are different, so an objective statistical data or market performance summary system limits a user's ability to make assessments and spot trends which are subjective and pertain to that individual's perspective vis-à-vis the information. One conventional approach to satisfying an individual's subjective information queries is through individual queries, such as quote searches and user-defined security watch lists. A drawback of individual queries and persistent query lists is that they limit a user's ability to compare and understand information in context with the overall data set or market.
One attempt to bridge the objective market performance gap was made by Martin Wattenberg of SmartMoney magazine. In his paper, Visualizing the Stock Market, Wattenberg described a two-dimensional data visualization algorithm capable of presenting detailed information on hundreds of items while emphasizing overall patterns in the data. This display method, which builds on Shneiderman's treemap technique, makes use of both hierarchy and similarity information. The display groups companies into rectangular-shaped sectors, with individual companies displayed as rectangles having an area proportional to market capitalization and dimensions optimized to be as close as possible to square. Each rectangle is filled with a color indicating the percent change of the stock's price since the most recent market close, with green indicating positive change, red indicating negative change, and black indicating lack of change. Within a sector, companies (rectangles) are ordered such that neighboring stocks are as similar as possible. In Wattenberg's model, similarity is derived from the percent price changes for each month of the past three years, which is represented by a point in 36-dimensional space. Within each sector, the layout chosen is the one that minimizes the sum of the distances between all pairs of adjacent rectangles. More details are provided in U.S. Pat. No. 6,583,794. Wattenberg implemented this approach in the Map of the Market, a web-based, tool that reports current data on 1000 publicly traded companies. Map of the Market is available at http://www.smartmoney.com/map-of-the-market.
While Wattenberg's Map of the Market addressed some of the inadequacy of earlier solutions, several drawbacks remain. First, the Map of the Market display is static and does not update automatically and dynamically. The user must update the display manually, which may take a substantial amount of time, thereby reducing the interactivity and utility of the application. Second, since Map of the Market is a web-based solution that is intended for display in a fixed window size of an Internet browser (e.g., Internet Explorer by Microsoft), the chosen way of sizing the rectangles representing individual stocks (i.e., by capitalization) means that certain stock tiles are less visible than others. In fact, the majority of the tiles are so small they are unable to include text or other discernible labeling or other information. This methodology occludes much of the activity data for a number of stocks contained in the set, and thereby makes it impossible for users to see or understand performance of those stocks which do not have sufficient market capitalization to be fully visible to users. Therefore the methodology's utility in displaying performance context is reduced to a data set of solely the largest cap stocks in sectors rather than a wider array. Third, the use of the fixed-size browser window for displaying Map of the Market restricts its usefulness and also makes it incompatible with newer user-interface technologies, e.g., touch screens, that allow the user to navigate more easily among large amounts of data or information. What is needed, then, is a method for visualizing a large collection of financial or other statistical information that overcomes these and other drawbacks of the prior art methods.